Jiancheng Zou¹, Jiaxin Li^1,*, Juncun Wei¹, Zhengzheng Li¹, Xin Yang²

Journal on Artificial Intelligence, Vol.3, No.3, pp. 123-134, 2021, DOI:10.32604/jai.2021.027069

Abstract Facial expression recognition is a research hot spot in the fields of computer vision and pattern recognition. However, the existing facial expression recognition models are mainly concentrated in the visible light environment. They have insufficient generalization ability and low recognition accuracy, and are vulnerable to environmental changes such as illumination and distance. In order to solve these problems, we combine the advantages of the infrared and visible images captured simultaneously by array equipment our developed with two infrared and two visible lens, so that the fused image not only has the texture information of visible image, but also has the… More >

Hao Chen^*, Qian Tang, Yifei Wei, Mei Song

Journal on Artificial Intelligence, Vol.3, No.3, pp. 115-121, 2021, DOI:10.32604/jai.2021.026851

Abstract As the cost of accessing a telecom operator’s network continues to decrease, user churn after arrears occurred repeatedly, which has brought huge economic losses to operators and reminded them that it is significant to identify users who are likely to churn in advance. Machine learning can form a series of judgment rules by summarizing a large amount of data, and telecom user data naturally has the advantage of user scale, which can provide data support for learning algorithms. XGBoost is an improved gradient boosting algorithm, and in this paper, we explore how to use the algorithm to train an efficient… More >

Saqlain Abbas^1,2,*, Zulkarnain Abbas³, Xiaotong Tu⁴, Yanping Zhu¹

Journal on Artificial Intelligence, Vol.3, No.3, pp. 97-113, 2021, DOI:10.32604/jai.2021.023020

Abstract The performance and reliability of structural components are greatly influenced by the presence of any abnormality in them. To this purpose, structural health monitoring (SHM) is recognized as a necessary tool to ensure the safety precautions and efficiency of both mechanical and civil infrastructures. Till now, most of the previous work has emphasized the functioning of several SHM techniques and systematic changes in SHM execution. However, there exist insufficient data in the literature regarding the patent-based technological developments in the SHM research domain which might be a useful source of detailed information for worldwide research institutes. To address this research… More >

Asmaa E. E. Ali^*, Mofreh Mohamed Salem, Mahmoud Badway, Ali I. EL Desouky

Journal on Artificial Intelligence, Vol.3, No.3, pp. 81-96, 2021, DOI:10.32604/jai.2021.022433

Abstract Breast cancer (BrC) is now the world’s leading cause of death for women. Early detection and effective treatment of this disease are the only rescues to reduce BrC mortality. The prediction of BrC diseases is very difficult because it is not an individual disease but a mixture of various diseases. Many researchers have used different techniques such as classification, Machine Learning (ML), and Deep Learning (DL) of the prediction of the breast tumor into Benign and Malignant. However, still there is a scope to introduce appropriate techniques for developing and implementing a more effective diagnosis system. This paper proposes a… More >

Xian Zhou¹, Fei Wang², Ziyu Wang³, Yunfeng Xu^1,*

Energy Engineering, Vol.119, No.2, pp. 653-664, 2022, DOI:10.32604/ee.2022.019072

Abstract The reservoir is the networked rock skeleton of an oil and gas trap, as well as the generic term for the fluid contained within pore fractures and karst caves. Heterogeneity and a complex internal pore structure characterize the reservoir rock. By introducing the fractal permeability formula, this paper establishes a fractal mathematical model of oil-water two-phase flow in an oil reservoir with heterogeneity characteristics and numerically solves the mathematical model using the weighted least squares meshless method. Additionally, the method’s correctness is verified by comparison to the exact solution. The numerical results demonstrate that the fractal oil-water two-phase flow mathematical… More >

Joselito Olalo^*

Energy Engineering, Vol.119, No.2, pp. 555-567, 2022, DOI:10.32604/EE.2022.018864

Abstract Unlike plastic, biomass can also be converted and produce high quality of biofuel. Co-pyrolysis of coconut husk (CH) and laminated plastic packaging (LPP) were done in this study. Synergy between these two feedstock was calculated by using thermogravimetric (TGA) and derivative thermogravimetry (DTG) analysis. Different activation energies of the reactions in the co-pyrolysis of CH and LPP were evaluated using the Coats-Redfern method. Results showed an activation energy ranging from 8 to 37 kJ/mol in the different percentage composition of the co-pyrolysis. Also, thermal degradation happens in two-stages in the copyrolysis of CH and LPP, in which CH degrades at… More >

Kaihui Zhao^1,2, Wenchang Liu¹, Tonghuan Yin³, Ruirui Zhou⁴, Wangke Dai¹ and Gang Huang^5,*

Energy Engineering, Vol.119, No.2, pp. 767-780, 2022, DOI:10.32604/EE.2021.018617

Abstract This paper presents a novel model-free sliding mode control (MFSMC) method to improve the speed response of permanent magnet synchronous machine (PMSM) drive system. The ultra-local model (ULM) is first derived based on the input and the output of the PMSM. Then, the novel MFSMC method is presented, and the controller is designed based on ULM and MFSMC. A sliding mode observer (SMO) is constructed to estimate the unknown part of the ULM. The estimated unknown part is feedbacked to MFSMC controller to perform compensation for parameter perturbations and external disturbances. Compared with the sliding mode control (SMC) method, the… More >

Xiaolei Li^*

Energy Engineering, Vol.119, No.2, pp. 665-680, 2022, DOI:10.32604/ee.2022.019292

Abstract Aiming at the difficulty of rolling bearing fault diagnosis of wind turbine under noise environment, a new bearing fault identification method based on the Improved Anti-noise Residual Shrinkage Network (IADRSN) is proposed. Firstly, the vibration signals of wind turbine rolling bearings were preprocessed to obtain data samples divided into training and test sets. Then, a bearing fault diagnosis model based on the improved anti-noise residual shrinkage network was established. To improve the ability of fault feature extraction of the model, the convolution layer in the deep residual shrinkage network was replaced with a Dense-Net layer. To further improve the anti-noise… More >

Omar H. Abdalla^1,*, Gamal Abdel-Salam², Azza A. A. Mostafa³

Energy Engineering, Vol.119, No.2, pp. 569-589, 2022, DOI:10.32604/ee.2022.018693

Abstract Battery Energy Storage System (BESS) is one of the potential solutions to increase energy system flexibility, as BESS is well suited to solve many challenges in transmission and distribution networks. Examples of distribution network’s challenges, which affect network performance, are: (i) Load disconnection or technical constraints violation, which may happen during reconfiguration after fault, (ii) Unpredictable power generation change due to Photovoltaic (PV) penetration, (iii) Undesirable PV reverse power, and (iv) Low Load Factor (LF) which may affect electricity price. In this paper, the BESS is used to support distribution networks in reconfiguration after a fault, increasing Photovoltaic (PV) penetration,… More >

Xuehui Wang¹, Edward Wright¹, Zeyu Liu¹, Neng Gao^2,*, Ying Li³

Energy Engineering, Vol.119, No.2, pp. 801-814, 2022, DOI:10.32604/ee.2022.018241

Abstract The pulsating heat pipe is a very promising heat dissipation device to address the challenge of higher heat-flux electronic chips, as it is characterised by excellent heat transfer ability and flexibility for miniaturisation. To boost the application of PHP, reliable heat transfer performance evaluation models are especially important. In this paper, a heat transfer correlation was firstly proposed for closed PHP with various working fluids (water, ethanol, methanol, R123, acetone) based on collected experimental data. Dimensional analysis was used to group the parameters. It was shown that the average absolute deviation (AAD) and correlation coefficient (r) of the correlation were… More >